
"""simple docstring"""


import argparse

import torch

from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging


logging.set_verbosity_info()



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				Any:







       """simple docstring"""
       # Initialise PyTorch model
       UpperCamelCase       			=		BertConfig.from_json_file(UpperCAmelCase_					)
       print(F"Building PyTorch model from configuration: {config}"					)
       UpperCamelCase       			=		BertForPreTraining(UpperCAmelCase_					)

       # Load weights from tf checkpoint
       load_tf_weights_in_bert(UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)

       # Save pytorch-model
       print(F"Save PyTorch model to {pytorch_dump_path}"					)
       torch.save(model.state_dict()		,   UpperCAmelCase_					)


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE			  =  argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
      )
      parser.add_argument(
          """--bert_config_file""",
          default=None,
          type=str,
          required=True,
          help=(
              """The config json file corresponding to the pre-trained BERT model. \n"""
              """This specifies the model architecture."""
          ),
      )
      parser.add_argument(
          """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
      )
      SCREAMING_SNAKE_CASE			  =  parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)







"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


SCREAMING_SNAKE_CASE			  =  logging.get_logger(__name__)



class 	__a	(   _lowerCAmelCase						):






       def __init__(	self			:				str							,   *UpperCAmelCase_			:				str							,   **UpperCAmelCase_			:				Any      )->	None:







              """simple docstring"""
              warnings.warn(
                  "The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
                  " use YolosImageProcessor instead."							,   UpperCAmelCase_							,   )
              super().__init__(*UpperCAmelCase_							,   **UpperCAmelCase_      )





